Aurelie Herbelot Profile picture
Mar 14 12 tweets 3 min read
Today is my last day in a university position so I wanted to write a few things about #leavingacademia⬇️

On NLP, Computational Linguistics and Meaning. Above all: on loving your object of study and owning it. \1
I don't often post here. I’m not a great talker. Which is a real shame because my research field loves talking on social media. About big engineering feats, conference acceptance rates, one's own success or struggles. Although, I note, relatively little about language itself. \2
At the risk of sounding sentimental, I became a computational semanticist because I cared about meaning. Deeply. I wanted to know what it was, the same way others want to know about beetles, asteroids or gravitation. I wanted to do science. \3
Science is the human activity that seeks to explain and predict natural phenomena. It presupposes that you spend a lot of time observing your object of study. That you befriend it. That you handle it with great care, lest your touch might affect its natural properties. \4
Language is a phenomenon which can be investigated with computational models in myriads of ways. But again, it must be handled with care. You can't 'put language into a machine' any more than you can put a beetle in a machine (it will break your GPU *and* the beetle). \5
It seems we were unhappy about how long it took to pin language down. So we found that we could instead fake it. The engineering side of our field now loves building beetle-robots with a UTF-8 carapace. Which is fine by me. (As long as you call a robot a robot.) \6
While engineers play, the rest of us are presumably doing the science. The actual beetles. The actual language. Taking our time and appreciating that our questions will not be solved in this lifetime, but that we will have been as close to them as one can be... Not quite. \7
We instead spend time dismantling the metal beetle (which we perfectly know is not a real beetle), trying to find its heart. Is this a thorax? An antenna? No. But there must be *something* to be found because no scientist would study something that is not there. Right? \8
Like others, I had times of bitterness about all this. But it always disappeared when I allowed myself to daydream away from the buzz, when I felt I had some private time with language again. So I started to think that academia itself did not matter so much. And here we are. \9
Doubling up on sentimentality: I do not want to lose the relationship I have built to language and meaning over the years, and I feel remaining in my field is somehow damaging to that relationship. I guess Semantics and I need some time away. \10
There are many paths to being a scientist. But competing for attention and high rankings is not one of them. Language does not care about your H-index or the size of your LLM. It shouldn't be about us, it should be about *it*. \11
I suppose some people will ask 'what I am going to do now'🙂

I am going to do what I’ve always done. Spend some time with meaning. Tinker with single boards. Go find some beetles 🪲 \the end

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More from @ah__cl

Jan 23, 2022
Here's some flattened portion of semantic space. What do you call meaning? a) the labeled points; b) the black void around them? /1
It seems to me we often think of the labeled vectors as meanings. But of course, the label is just a name for a position in space. A word may vary its position depending on speaker, on the time at which the vector was constructed (diachronic change), on the age of the speaker. /2
Perhaps more interestingly, modality will move concepts in space. Instances of a kind may be one way, but could or should be another way. So would it be better to see a space as a superposition of possible worlds? And meaning as pervasive in that space? /3
Read 4 tweets
Sep 21, 2020
New pre-print with Katrin Erk:

"How to marry a star? Probabilistic constraints for meaning in context."

A theoretical paper on evocation: how people ‘imagine' an entire situation from a few words, and how meaning is contextualised in the process.

arxiv.org/abs/2009.07936 /1
#lightreading summary ⬇️

When you hear 'the batter ran to the ball', what do you imagine? A batter? A ball? But perhaps also a pitch, an audience, the sun and a cap on the head of the batter.

What do you imagine when you hear 'the duchess drove to the ball'? /2
We propose a computational model which takes a (simple) sentence and builds a conceptual description for it. In the process of doing so, it captures appropriate word senses or other lexical meaning variations. E.g. that the batter's ball is not a dancing event. /3
Read 11 tweets
Jan 18, 2020
Talking about #compositionality opens a giant can of worms. One worm: what is it that we compose and where does it come from? What is it that does composition, and where does it come from? I've tried to put some thoughts together on #innateness. /1

This thread has three parts: a) how some approaches to compositionality deal with innateness; b) why we should think about innateness in relation to computational models; c) why we should think about innateness in relation to data. /2
PART 1 - HISTORY. I previously mentioned that different approaches to composition have different relations to innateness. Let's get back to some obvious protagonists -- Chomsky, Katz & Fodor... And let's start with a turning point in the historical debate on innateness... /3
Read 32 tweets
Jan 11, 2020
Here's a thread surveying some 'classic' work on #compositionality. Lots of people seem to be discussing this right now, but with partial references to the whole story. My aim is to highlight some of the philosophical and psychological issues in the history of the concept. 1/
Small recap first... There are two principles usually associated with #compositionality, both (possibly incorrectly) attributed to Frege. See Pelletier's "Did Frege believe in Frege's principle?" (2001). 2/
1) Bottom-up, the 'compositionality principle': "... an important general principle which we shall discuss later under the name Frege's Principle, that the meaning of the whole sentence is a function of the meanings of its parts.'" Cresswell (1973) 3/
Read 32 tweets
Dec 20, 2019
As we reflect on 2019 and decide on our research directions for 2020, here's a summary of my recent reading. The #context tag tells you *why* I ended up there (thx to @julianharris for the tag suggestion ;)). I'm curious to know what other people's journeys have been this year...
Reading list (1) Language evolution papers. #context I am still trying to figure out what exactly language is for. We've seen some cool work on meaning shift in the last years. But *why* do meanings shift? And what does it tell us about the role of language in human behaviour?
Reading list (2) Papers on aligning vector spaces. #context the whole "let's average the utterance of thousands of speakers in a big corpus and pretend it's language" is rather tedious. My semantic space in not your semantic space. But how best to measure such differences?
Read 7 tweets
Dec 14, 2019
This thread made me think. Not about *what* we read but about *why* we read.
I personally find it extremely hard to recommend papers to others because the papers I most cherish are not necessarily relevant to the world at large, and they might not even be what your standard reviewer would consider 'a good paper'.
I cherish papers that connect things I'm thinking about. They're puzzle pieces that fit my own puzzle and may well be totally useless to someone else's puzzle. And sometimes it's not about the whole paper. The missing puzzle piece may be in a single paragraph or a footnote.
Read 7 tweets

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